Quantifying the uncertainty in estimates of surface–atmosphere fluxes through joint evaluation of the SEBS and SCOPE models

J Timmermans,C Van Der Tol,W Verhoef,A Verhoef,Z Su

doi:10.5194/hess-17-1561-2013

Abstract

Abstract. Accurate estimation of global evapotranspiration is considered to be of great importance due to its key role in the terrestrial and atmospheric water budget. Global estimation of evapotranspiration on the basis of observational data can only be achieved by using remote sensing. Several algorithms have been developed that are capable of estimating the daily evapotranspiration from remote sensing data. Evaluation of remote sensing algorithms in general is problematic because of differences in spatial and temporal resolutions between remote sensing observations and field measurements. This problem can be solved in part by using soil-vegetation-atmosphere transfer (SVAT) models, because on the one hand these models provide evapotranspiration estimations also under cloudy conditions and on the other hand can scale between different temporal resolutions. In this paper, the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model is used for the evaluation of the Surface Energy Balance System (SEBS) model. The calibrated SCOPE model was employed to simulate remote sensing observations and to act as a validation tool. The advantages of the SCOPE model in this validation are (a) the temporal continuity of the data, and (b) the possibility of comparing different components of the energy balance. The SCOPE model was run using data from a whole growth season of a maize crop. It is shown that the original SEBS algorithm produces large uncertainties in the turbulent flux estimations caused by parameterizations of the ground heat flux and sensible heat flux. In the original SEBS formulation the fractional vegetation cover is used to calculate the ground heat flux. As this variable saturates very fast for increasing leaf area index (LAI), the ground heat flux is underestimated. It is shown that a parameterization based on LAI reduces the estimation error over the season from RMSE = 25 W m−2 to RMSE = 18 W m−2. In the original SEBS formulation the roughness height for heat is only valid for short vegetation. An improved parameterization was implemented in the SEBS algorithm for tall vegetation. This improved the correlation between the latent heat flux predicted by the SEBS and the SCOPE algorithm from −0.05 to 0.69, and led to a decrease in difference from 123 to 94 W m−2 for the latent heat flux, with SEBS latent heat being consistently lower than the SCOPE reference. Lastly the diurnal stability of the evaporative fraction was investigated.

Highlights

Accurate estimation of evapotranspiration, ET, is considered of great importance due to its key role in hydrology and meteorology
Evapotranspiration cannot be detected directly from space. This has lead to a large variety in remote sensing algorithms that estimate ET from variables that are observable from space
The advantage of simulating band radiances enables simulation of remote sensing imagery during cloudy days when actual optical sensors only will measure clouds. This enables the estimation of evapotranspiration for dates when there is no remote sensing observation and is suitable for creating long time series

Summary

Introduction

ET, is considered of great importance due to its key role in hydrology and meteorology It is involved in many feedback mechanisms, for example between the water and the energy balance, and between the land surface and the atmosphere. Evapotranspiration cannot be detected directly from space This has lead to a large variety in remote sensing algorithms that estimate ET from variables that are observable from space. These methods range from triangle/trapezoidal (Carlson, 2007) methods to the use of reference ET (by Penman-Monteith/Priestley Tailor) together with crop coefficients to energy balance (residual) algorithms (Kalma et al, 2008; Glenn et al, 2007).

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